The Hiatus Between Organism and Machine Evolution: Contrasting Mixed Microbial Communities with Robots

IF 1.2 Q3 Computer Science
A. Roli, S. Kauffman
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引用次数: 2

Abstract

Mixed microbial communities, usually composed of various bacterial and fungal species, are fundamental in a plethora of environments, from soil to human gut and skin. Their evolution is a paradigmatic example of intertwined dynamics, where not just the relations among species plays a role, but also the opportunities-and possible harms-that each species presents to the others. These opportunities are in fact affordances, which can be seized by heritable variations and selection. In this paper, starting from a systemic viewpoint of mixed microbial communities, we focus on the pivotal role of affordances in evolution and we contrast it to the artificial evolution of programs and robots. We maintain that the two realms are neatly separated, in that natural evolution proceeds by extending the space of its possibilities in a completely open way, while the latter is inherently limited by the algorithmic framework in which it is defined. This discrepancy characterises also an envisioned setting in which robots evolve in the physical world. We present arguments supporting our claim and we propose an experimental setting for assessing our statements. Rather than just discussing the limitations of the artificial evolution of machines, the aim of this contribution is to emphasize the tremendous potential of the evolution of the biosphere, beautifully represented by the evolution of communities of microbes.
有机体与机器进化之间的间隙:混合微生物群落与机器人的对比
混合微生物群落通常由各种细菌和真菌物种组成,是从土壤到人体肠道和皮肤等众多环境的基础。它们的进化是一个相互交织的动力学的典型例子,不仅物种之间的关系起着作用,而且每个物种给其他物种带来的机会和可能的危害也起着作用。这些机会实际上是可以通过遗传变异和选择获得的资源。在本文中,我们从混合微生物群落的系统观点出发,重点讨论了在进化中的关键作用,并将其与程序和机器人的人工进化进行了对比。我们认为,这两个领域是完全分开的,因为自然进化是通过以完全开放的方式扩展其可能性空间来进行的,而后者本质上受到定义它的算法框架的限制。这种差异也体现了机器人在现实世界中进化的设想。我们提出的论据支持我们的主张,我们提出了一个实验设置来评估我们的陈述。这篇文章的目的不是仅仅讨论机器人工进化的局限性,而是强调生物圈进化的巨大潜力,微生物群落的进化完美地体现了这一点。
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来源期刊
Bio-Algorithms and Med-Systems
Bio-Algorithms and Med-Systems MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
3.80
自引率
0.00%
发文量
3
期刊介绍: The journal Bio-Algorithms and Med-Systems (BAMS), edited by the Jagiellonian University Medical College, provides a forum for the exchange of information in the interdisciplinary fields of computational methods applied in medicine, presenting new algorithms and databases that allows the progress in collaborations between medicine, informatics, physics, and biochemistry. Projects linking specialists representing these disciplines are welcome to be published in this Journal. Articles in BAMS are published in English. Topics Bioinformatics Systems biology Telemedicine E-Learning in Medicine Patient''s electronic record Image processing Medical databases.
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